Why AI Projects Fail and How Leaders Can Get It Right | Kathleen Walch

Why do so many AI projects stall out, overspend, or quietly fail inside organizations?

In this episode of Executive Connect, Melissa Aarskaug sits down with Kathleen Walch, leader at the Project Management Institute and co-creator of the CPMAI methodology, to talk about what actually makes AI succeed. Kathleen explains why AI failure is rarely just a tech problem and why leadership, change management, data quality, workflow design, and trust matter far more than most teams realize. She also shares what strong organizations do differently before they invest, how leaders can spot failure early, and why AI literacy has to become part of the culture.

If your company is experimenting with AI, rolling out copilots, or trying to move from hype to business value, this episode will help you approach it with more clarity and fewer expensive mistakes.


What You’ll Learn

• Why most AI failures are people and process failures
• The early warning signs an AI project is going off track
• Why AI should not sit only inside IT
• How to think about ROI before approving AI spend
• Why AI literacy matters more than most leaders think
• What successful organizations do before deployment
• How to build trust, governance, and adoption across teams

Chapters

(0:00) Why leaders must stop waiting
(0:29) Kathleen Walch on AI execution
(1:23) Why AI is change management
(2:31) What leaders underestimate most
(6:58) Why AI is not just IT
(9:27) The top reasons AI projects fail
(11:57) Early warning signs before failure
(14:11) Who owns AI outcomes
(15:44) How leaders quietly block progress
(18:17) Where hierarchy slows AI learning
(21:51) What successful organizations do first
(25:47) Why so many AI projects fail
(29:02) How to build trustworthy AI
(32:25) What leaders should start now
(37:42) The AI myth leaders must drop
(43:16) Final advice and where to connect


Guest Bio

Kathleen Walch is a leader at the Project Management Institute and co-creator of the CPMAI methodology, a framework built to help organizations run and manage AI projects more effectively. She has spent the last decade working at the intersection of AI strategy, execution, education, and change management, helping leaders move AI from hype into real business value.

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